Abstract

Several different methods exist for efficient approximation of paths
in multiscale stochastic chemical systems. Another approach is to
use bursts of stochastic simulation to estimate the parameters of a
stochastic differential equation approximation of the paths. In this
paper, multiscale methods for approximating paths are used to
formulate different strategies for estimating the dynamics by
diffusion processes. We then analyse how efficient and accurate
these methods are in a range of different scenarios, and compare
their respective advantages and disadvantages to other methods
proposed to analyse multiscale chemical networks.